Diagnosis of fetal arrhythmia in echocardiography imaging using deep learning with cyclic loss.

Background: Fetal arrhythmias frequently co-occur with congenital heart disease in fetuses. The peaks observed in M-mode fetal echocardiograms serve as pivotal diagnostic markers for fetal arrhythmias. However, speckles, artifacts, and noise pose notable challenges for accurate image analysis.

Applications of artificial intelligence-powered prenatal diagnosis for congenital heart disease.

Artificial intelligence (AI) has made significant progress in the medical field in the last decade. The AI-powered analysis methods of medical images and clinical records can now match the abilities of clinical physicians. Due to the challenges posed by the unique group of fetuses and the dynamic organ of the heart, research into the application of AI in the prenatal diagnosis of congenital heart disease (CHD) is particularly active.

Quantitative Trait Locus Mapping of Marsh Spot Disease Resistance in Cranberry Common Bean ( L.).

Common bean ( L.) is a food crop that is an important source of dietary proteins and carbohydrates. Marsh spot is a physiological disorder that diminishes seed quality in beans.

Genome-wide identification of ATP binding cassette (ABC) transporter and heavy metal associated (HMA) gene families in flax (Linum usitatissimum L.).

Background: The recent release of the reference genome sequence assembly of flax, a self-pollinated crop with 15 chromosome pairs, into chromosome-scale pseudomolecules enables the characterization of gene families. The ABC transporter and HMA gene families are important in the control of cadmium (Cd) accumulation in crops. To date, the genome-wide analysis of these two gene families has been successfully conducted in some plant species, but no systematic evolutionary analysis is available for the flax genome.